Results 51 to 60 of about 1,022,373 (272)
Topic Models with Topic Ordering Regularities for Topic Segmentation [PDF]
Documents from the same domain usually discuss similar topics in a similar order. In this paper we present new ordering-based topic models that use generalised Mallows models to capture this regularity to constrain topic assignments. Specifically, these new models assume that there is a canonical topic ordering shared amongst documents from the same ...
Lan Du, Mark Johnson, John K. Pate
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Topic Modelling: Going beyond Token Outputs
Topic modelling is a text mining technique for identifying salient themes from a number of documents. The output is commonly a set of topics consisting of isolated tokens that often co-occur in such documents.
Lowri Williams+3 more
doaj +1 more source
Visualizing Topic Uncertainty in Topic Modelling
Word clouds became a standard tool for presenting results of natural language processing methods such as topic modelling. They exhibit most important words, where word size is often chosen proportional to the relevance of words within a topic. In the latent Dirichlet allocation (LDA) model, word clouds are graphical presentations of a vector of weights
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Sequential Topic Selection Model with Latent Variable for Topic-Grounded Dialogue [PDF]
Recently, topic-grounded dialogue system has attracted significant attention due to its effectiveness in predicting the next topic to yield better responses via the historical context and given topic sequence. However, almost all existing topic prediction solutions focus on only the current conversation and corresponding topic sequence to predict the ...
arxiv
Two-stage topic modelling of scientific publications: A case study of University of Nairobi, Kenya.
Unsupervised statistical analysis of unstructured data has gained wide acceptance especially in natural language processing and text mining domains. Topic modelling with Latent Dirichlet Allocation is one such statistical tool that has been successfully ...
Leacky Muchene, Wende Safari
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Topic Taxonomy Expansion via Hierarchy-Aware Topic Phrase Generation [PDF]
Topic taxonomies display hierarchical topic structures of a text corpus and provide topical knowledge to enhance various NLP applications. To dynamically incorporate new topic information, several recent studies have tried to expand (or complete) a topic taxonomy by inserting emerging topics identified in a set of new documents.
arxiv
More than a feeling? What does compassion in healthcare ‘look like’ to patients?
Objective Compassion is important to patients and their families, predicts positive patient and practitioner outcomes, and is a professional requirement of physicians around the globe.
Sofie I. Baguley+2 more
doaj +1 more source
BERTopic: Neural topic modeling with a class-based TF-IDF procedure [PDF]
Topic models can be useful tools to discover latent topics in collections of documents. Recent studies have shown the feasibility of approach topic modeling as a clustering task. We present BERTopic, a topic model that extends this process by extracting coherent topic representation through the development of a class-based variation of TF-IDF.
arxiv
Evaluation methods for topic models [PDF]
A natural evaluation metric for statistical topic models is the probability of held-out documents given a trained model. While exact computation of this probability is intractable, several estimators for this probability have been used in the topic modeling literature, including the harmonic mean method and empirical likelihood method.
Wallach, Hanna M.+3 more
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In vivo IL‐10 produced by tissue‐resident tolDC is involved in maintaining/inducing tolerance. Depending on the agent used for ex vivo tolDC generation, cells acquire common features but prime T cells towards anergy, FOXP3+ Tregs, or Tr1 cells according to the levels of IL‐10 produced. Ex vivo‐induced tolDC were administered to patients to re‐establish/
Konstantina Morali+3 more
wiley +1 more source